code: def test_byte_permutation() -> None:
      opts = argparse.Namespace()
  
      t = image_bytes.BytePermutation(opts)
  
      size = 32
      samples = torch.randint(255, [size])
      x = {"samples": samples.clone()}
      out = t(x)["samples"]
      assert out.shape == samples.shape
      assert samples.unique().shape == out.unique().shape
  
file_path: ml-cvnets/tests/transforms/test_image_bytes.py
imports: import argparse
  from typing import Tuple
  import pytest
  import torch
  from data.transforms import image_bytes
label_desc: Use image node_id 4 for calling a global function with example usage: test_byte_permutation() without return types